AI Innovation & Prototyping Engineer (GenAI / Agentic AI)

Opportunity Description AI Innovation & Prototyping Engineer (GenAI / Agentic AI)

Our end client a technology and digital transformation organization focused on delivering innovative IT solutions and consulting services helps businesses leverage emerging technologies to modernize operations, accelerate innovation, and build scalable digital capabilities. The organization provides opportunities to work on next-generation technology initiatives in a dynamic, innovation-driven environment.

They are looking for an AI Innovation & Prototyping Engineer (GenAI / Agentic AI) to explore, design, and rapidly prototype innovative AI-powered solutions. The role involves building Generative AI applications, developing agentic AI workflows, experimenting with LLMs and AI frameworks, and transforming proof-of-concepts into scalable solutions. This is an exciting opportunity for professionals passionate about emerging AI technologies, rapid experimentation, and solving real-world business challenges through intelligent automation.

Roles & Responsibilities :

• Continuously explore and experiment with the latest AI tools, platforms, applications and emerging technologies.
• Work directly with senior management to understand business problems and identify opportunities for AI-driven solutions.
• Develop rapid prototypes and Proof of Concepts (POCs) using Generative AI, Agentic AI and AI-powered development tools.
• Build AI-powered applications, intelligent assistants, automation workflows and business productivity solutions.
• Experiment with LLMs, AI agents, multi-agent workflows, prompt engineering and RAG-based applications.
• Leverage AI coding tools such as Cursor, GitHub Copilot, Claude Code, OpenAI Codex and similar platforms.
• Build and integrate solutions using Python, APIs, databases and third-party applications.
• Explore workflow automation platforms such as n8n, Make, Zapier, Dify and Flowise.
• Evaluate emerging AI technologies and recommend suitable solutions for real-world business use cases.
• Present prototypes and solution demonstrations to senior management and incorporate feedback.
• Continuously learn, experiment and adopt new technologies to improve solution capabilities.

Required Skills & Technical Exposure

Artificial Intelligence & GenAI:

• Good understanding of Generative AI, LLMs and Prompt Engineering.
• Hands-on exposure to ChatGPT, Claude, Gemini, Perplexity or similar AI platforms.
• Familiarity with OpenAI APIs, Gemini APIs or Anthropic APIs.
• Basic understanding of AI Agents, Agentic AI and RAG concepts.

Programming & Development:

• Basic to good programming skills in Python.
• Exposure to JavaScript / TypeScript, Node.js or other programming languages.
• Understanding of REST APIs, JSON, database connectivity and application integration.
• Exposure to FastAPI, Flask or Streamlit is an advantage.

AI Tools & Automation:

• Familiarity with AI coding assistants such as Cursor, GitHub Copilot, Claude Code or Codex.
• Exposure to n8n, Make, Zapier, Dify, Flowise or similar automation platforms.
• Interest in exploring LangChain, LangGraph, CrewAI and MCP.
• Exposure to AI-powered application builders such as Replit, Lovable or Bolt.

Candidate Profile

• 2 - 5 years of experience in Software Development, Python Development, AI/ML, Automation or Application Development.
• Strong passion for Artificial Intelligence and emerging technologies.
• Demonstrable experience experimenting with AI tools and building applications or prototypes.
• Ability to quickly learn new technologies and independently develop working solutions.
• Strong analytical thinking, creativity and problem-solving capabilities.
• Good communication skills and confidence in interacting with senior management.
• Self-motivated, curious and willing to explore technologies beyond conventional development environments.

Preferred Qualifications

• B.Tech / B.E. / M.Tech in Computer Science, IT, Electronics or related disciplines.
• Candidates with personal AI projects, GitHub repositories, working prototypes or independent AI experiments will be preferred.
• Exposure to cloud platforms, Docker, GitHub and application deployment is an added advantage.